Learning to Master OpenCV 3 in Python
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102 Lectures
10h 7m
Prepare for your examination with our training course. The course contains a complete batch of videos that will provide you with profound and thorough knowledge related to certification exam. Pass the test with flying colors.
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Curriculum For This Course
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1. Introduction2m
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2. Introduction to Computer Vision and OpenCV3m
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3. About this course5m
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4. Recomended - Setup your OpenCV4.0.1 Virtual Machine6m
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5. Set up course materials (DOWNLOAD LINK BELOW) - Not needed if using the new VM2m
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1. What are Images?2m
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2. How are Images Formed?3m
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3. Storing Images on Computers5m
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4. Getting Started with OpenCV - A Brief OpenCV Intro9m
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5. Grayscaling - Converting Color Images To Shades of Gray2m
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6. Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally12m
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7. Histogram representation of Images - Visualizing the Components of Images5m
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8. Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text4m
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1. Transformations, Affine And Non-Affine - The Many Ways We Can Change Images2m
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2. Image Translations - Moving Images Up, Down3m
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3. Rotations - How To Spin Your Image Around And Do Horizontal Flipping3m
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4. Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality4m
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5. Image Pyramids - Another Way of Re-Sizing2m
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6. Cropping - Cut Out The Image The Regions You Want or Don't Want3m
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7. Arithmetic Operations - Brightening and Darkening Images4m
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8. Bitwise Operations - How Image Masking Works4m
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9. Blurring - The Many Ways We Can Blur Images & Why It's Important7m
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10. Sharpening - Reverse Your Images Blurs2m
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11. Thresholding (Binarization) - Making Certain Images Areas Black or White9m
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12. Dilation, Erosion, Opening/Closing - Importance of Thickening/Thinning Lines5m
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13. Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down4m
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14. Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing5m
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1. Segmentation and Contours - Extract Defined Shapes In Your Image11m
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2. Sorting Contours - Sort Those Shapes By Size13m
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3. Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours6m
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4. Matching Contour Shapes - Match Shapes In Images Even When Distorted5m
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5. Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars)5m
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6. Line Detection - Detect Straight Lines E.g6m
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7. Blob Detection - Detect The Center of Flowers3m
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8. Mini Project 3 - Counting Circles and Ellipses6m
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1. Object Detection Overview3m
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2. Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image)3m
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3. Feature Description Theory - How We Digitally Represent Objects5m
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4. Finding Corners - Why Corners In Images Are Important to Object Detection7m
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5. SIFT, SURF, FAST, BRIEF & ORB - Learn The Different Ways To Get Image Features10m
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6. Mini Project 5 - Object Detection - Detect A Specific Object Using Your Webcam15m
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7. Histogram of Oriented Gradients - Another Novel Way Of Representing Images8m
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1. HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing5m
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2. Face and Eye Detection - Detect Human Faces and Eyes In Any Image11m
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3. Mini Project 6 - Car and Pedestrian Detection in Videos7m
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1. Face Analysis and Filtering - Identify Face Outline, Lips, Eyes Even Eyebrows11m
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2. Merging Faces (Face Swaps) - Combine Two Faces For Fun & Sometimes Scary Results9m
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3. Mini Project 7 - Live Face Swapper (like MSQRD & Snapchat filters!!!)6m
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4. Mini Project 8 - Yawn Detector and Counter9m
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1. Machine Learning Overview - What Is It & Why It's Important to Computer Vision9m
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2. Mini Project 9 - Handwritten Digit Classification20m
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3. Mini Project # 10 - Facial Recognition - Make Your Computer Recognize You12m
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1. Filtering by Color6m
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2. Background Subtraction and Foreground Subtraction7m
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3. Using Meanshift for Object Tracking5m
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4. Using CAMshift for Object Tracking4m
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5. Optical Flow - Track Moving Objects In Videos7m
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6. Mini Project # 11 - Ball Tracking5m
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1. Mini Project # 12 - Photo-Restoration7m
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1. Course Summary and how to become an Expert3m
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2. Latest Advances, 12 Startup Ideas & Implementing Computer VIsion inm Mobile Apps7m
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1. Setup your Deep Learning Virtual Machine10m
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2. Intro to Handwritten Digit Classification (MNIST)6m
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3. Intro to Multiple Image Classification (CIFAR10)3m
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1. Neural Networks Chapter Overview2m
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2. Machine Learning Overview8m
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3. Neural Networks Explained4m
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4. Forward Propagation9m
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5. Activation Functions9m
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6. Training Part 1 – Loss Functions9m
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7. Training Part 2 – Backpropagation and Gradient Descent10m
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8. Backpropagation & Learning Rates – A Worked Example14m
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9. Regularization, Overfitting, Generalization and Test Datasets15m
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10. Epochs, Iterations and Batch Sizes4m
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11. Measuring Performance and the Confusion Matrix7m
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12. Review and Best Practices4m
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1. Convolutional Neural Networks Chapter Overview1m
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2. Introduction to Convolutional Neural Networks (CNNs)5m
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3. Convolutions & Image Features13m
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4. Depth, Stride and Padding7m
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5. ReLU2m
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6. Pooling5m
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7. The Fully Connected Layer2m
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8. Training CNNs3m
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9. Designing Your Own CNN4m
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1. Introduction to Keras & Tensorflow1m
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2. Building a CNN in Keras12m
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3. Building a Handwriting Recognition CNN2m
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4. Loading Our Data6m
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5. Getting our data in ‘Shape’4m
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6. Hot One Encoding3m
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7. Building & Compiling Our Model4m
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8. Training Our Classifier5m
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9. Plotting Loss and Accuracy Charts3m
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10. Saving and Loading Your Model3m
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11. Displaying Your Model Visually3m
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12. Building a Simple Image Classifier using CIFAR107m
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1. Data Augmentation Chapter Overview1m
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2. Splitting Data into Test and Training Datasets10m
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3. Train a Cats vs4m
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4. Boosting Accuracy with Data Augmentation5m
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5. Types of Data Augmentation5m
